revise argument isolates in clustcoef()

NEWS.md

@@ -5,8 +5,10 @@ Printing
 + Fixed a typo when printing the parameters of the default preference function.
 
 Interface
-+ Moved the logical argument `directed` in `rpanet` into `initial.network`;
++ Moved the logical argument `directed` in `rpanet()` into `initial.network`;
   `rpanet(nstep = 1e4, initial.network = list(directed = TRUE))`.
++ Revised argument `isolates` in `clustcoef()` to binary.
+
 
 # wdnet 1.1.0
 

R/centrality.R

@@ -61,7 +61,7 @@ degree_c <- function(adj, alpha = 1, mode = "out") {
     if (isSymmetric(adj) == TRUE) {
       warning("The analyzed network is undirected!")
     }
-    deg_c_output <- matrix(NA, nrow = dim(adj)[1], ncol = 2)
+    deg_c_output <- matrix(NA_real_, nrow = dim(adj)[1], ncol = 2)
     adj_name <- colnames(adj)
     if (is.null(adj_name) == FALSE) {
       deg_c_output <- adj_name
@@ -126,7 +126,7 @@ closeness_c <- function(adj, alpha = 1, mode = "out",
   if (dim(adj)[1] != dim(adj)[2]) {
     stop("The adjacency matrix must be a square matrix!")
   } else {
-    closeness_c_output <- matrix(NA, nrow = dim(adj)[1], ncol = 2)
+    closeness_c_output <- matrix(NA_real_, nrow = dim(adj)[1], ncol = 2)
     adj_name <- colnames(adj)
     if (is.null(adj_name) == FALSE) {
       closeness_c_output[, 1] <- adj_name

R/clustercoef.R

@@ -26,18 +26,18 @@ NULL
 #' @param netwk A \code{wdnet} object that represents the network. If
 #'   \code{NULL}, the function will compute the coefficient using either
 #'   \code{edgelist}, \code{edgeweight}, or \code{adj}.
-#' @param edgelist  A two column matrix, each row represents a directed edge of
+#' @param edgelist  A two-column matrix, each row represents a directed edge of
 #'   the network.
 #' @param edgeweight A vector representing the weight of edges.
 #' @param adj An adjacency matrix of a weighted and directed network.
 #' @param directed Logical. Indicates whether the edges in \code{edgelist} or
 #'   \code{adj} are directed.
-#' @param method which method used to compute clustering coefficients: Clemente
+#' @param method Which method used to compute clustering coefficients: Clemente
 #'   and Grassi (2018) or Fagiolo (2007).
-#' @param isolates character, defines how to treat vertices with degree zero and
-#'   one. If "zero", then their clustering coefficient is returned as 0 and are
+#' @param isolates Binary, defines how to treat vertices with degree zero and
+#'   one. If 0, then their clustering coefficient is returned as 0 and are
 #'   included in the averaging. Otherwise, their clustering coefficient is \code{NaN}
-#'   and are excluded in the averaging. Default value is "zero".
+#'   and are excluded in the averaging. Default value is 0.
 #'
 #' @return Lists of local clustering coefficients (in terms of a vector), global
 #'   clustering coefficient (in terms of a scalar) and number of weighted
@@ -82,7 +82,7 @@ clustcoef <- function(
     adj,
     directed = TRUE,
     method = c("Clemente", "Fagiolo"),
-    isolates = "zero") {
+    isolates = 0) {
   if (missing(adj)) {
     netwk <- create_wdnet(
       netwk = netwk,
@@ -173,6 +173,10 @@ clustcoef <- function(
     "cycle" = numTriangles$"cycle" / denomMiddle
   )
   if (isolates == "zero") {
+    cat('Argument "isolates" has been revised; use "isolates = 0" instead.\n"')
+    isolates <- 0
+  }
+  if (isolates == 0) {
     localcc <- rapply(localcc, function(i) ifelse(is.na(i), 0, i),
       how = "replace"
     )

R/joint_dist.R

@@ -352,10 +352,10 @@ get_eta_directed <- function(
 #' @param edgelist A two column matrix representing the undirected edges of a
 #'   network.
 #' @param target.assortcoef Numeric, represents the predetermined assortativity
-#'   coefficient. If \code{NA}, the range of assortativity coefficient and
+#'   coefficient. If \code{NULL}, the range of assortativity coefficient and
 #'   corresponding joint distribution are returned.
 #' @param eta.obj A convex function of \code{eta} to be minimized when
-#'   \code{target.assortcoef} is not \code{NA}. Defaults to 0.
+#'   \code{target.assortcoef} is not \code{NULL}. Defaults to 0.
 #' @param control A list of parameters passed to \code{CVXR::solve()} when
 #'   solving for \code{eta} or computing the range of assortativity coefficient.
 #'

R/rewire.R

@@ -92,10 +92,10 @@ dprewire_directed <- function(
   )
   rho <- data.frame(
     "Iteration" = c(0:iteration),
-    "outout" = NA,
-    "outin" = NA,
-    "inout" = NA,
-    "inin" = NA
+    "outout" = NA_real_,
+    "outin" = NA_real_,
+    "inout" = NA_real_,
+    "inin" = NA_real_
   )
   rho[1, 2:5] <- c(
     "outout" = stats::cor(sout, tout),
@@ -169,7 +169,7 @@ dprewire_undirected <- function(
     eta, rewire.history
   )
   rm(node1, node2, degree1, degree2, index1, index2)
-  rho <- data.frame("Iteration" = c(0:iteration), "Value" = NA)
+  rho <- data.frame("Iteration" = c(0:iteration), "Value" = NA_real_)
   rho[1, 2] <- assortcoef(edgelist = edgelist, directed = FALSE)
   rho[2:(iteration + 1), 2] <- ret$rho
   colnames(rho) <- c("Iteration", "Value")